|
|
Absolute deviation, 绝对离差
+ \* F M7 C& kAbsolute number, 绝对数
" k+ t: V$ \5 i; J5 S# I SAbsolute residuals, 绝对残差0 |- Z) V3 S4 P: _
Acceleration array, 加速度立体阵' C+ A- T# F5 t! Z( W" A2 a
Acceleration in an arbitrary direction, 任意方向上的加速度
8 h( I( A+ ?8 J. |( ^% ?/ \Acceleration normal, 法向加速度
^) U7 n8 h1 Y, |- CAcceleration space dimension, 加速度空间的维数6 A" U0 H* A$ R" y* u, l
Acceleration tangential, 切向加速度* Y$ [& b2 v) A: K0 F5 e
Acceleration vector, 加速度向量
# I8 M2 c% n0 I' EAcceptable hypothesis, 可接受假设! j) S8 n7 ^& }/ T+ q7 d& L6 N* A
Accumulation, 累积/ {; V0 D% a0 x9 V B8 x
Accuracy, 准确度) T! K2 e2 P+ A% j3 T- j
Actual frequency, 实际频数* D- l3 h0 i1 U1 ?* w( j( F
Adaptive estimator, 自适应估计量
t7 Z+ Y. r; g* [Addition, 相加
& c: o$ n- J/ eAddition theorem, 加法定理
2 w- Y" o" n3 b" uAdditivity, 可加性
4 w; d) ~. |8 W5 |. }$ h& u R6 Y) LAdjusted rate, 调整率
" L5 }4 o% Q- F6 h B6 G$ ] IAdjusted value, 校正值
8 }3 A0 K- q. W5 C2 h+ {# {: [Admissible error, 容许误差
4 p) h) R2 z! [) U t7 IAggregation, 聚集性' _6 V2 M5 `2 g
Alternative hypothesis, 备择假设 G; n5 n8 T. w
Among groups, 组间0 }2 p! K ~0 j3 ^- L W5 r
Amounts, 总量" h1 L3 }- l2 j) x }4 C
Analysis of correlation, 相关分析
* I# `* X& m9 {8 `Analysis of covariance, 协方差分析" D: Z" N5 Q7 \
Analysis of regression, 回归分析4 v2 b* [% L" y3 W
Analysis of time series, 时间序列分析
" Q! Q% g9 ~6 m8 v/ o* T. o4 T tAnalysis of variance, 方差分析
$ R; x& h* H7 t! y+ ]7 H; r/ \Angular transformation, 角转换
- O' M* e+ H; }$ YANOVA （analysis of variance）, 方差分析
' |8 `- H0 E1 M4 W+ AANOVA Models, 方差分析模型
, [6 x( i7 C( f: YArcing, 弧/弧旋0 p) W/ T- s/ ]1 z
Arcsine transformation, 反正弦变换
5 B; A2 w' \4 l; ]1 C8 O" u/ ?Area under the curve, 曲线面积( P5 b5 f, ^& j- G
AREG , 评估从一个时间点到下一个时间点回归相关时的误差 0 R/ L1 `6 y0 ]8 d; c, e* O H
ARIMA, 季节和非季节性单变量模型的极大似然估计
" {6 p2 a! l8 D J H& _: ~Arithmetic grid paper, 算术格纸4 g8 ]5 D' a" T- K
Arithmetic mean, 算术平均数! o# f4 a+ [. S5 }7 A E- v( O
Arrhenius relation, 艾恩尼斯关系8 V8 \: Z4 z" [2 j) a7 w, `. U8 A& n
Assessing fit, 拟合的评估
0 A3 M7 B/ D! pAssociative laws, 结合律1 ^: y3 }8 |! N& \
Asymmetric distribution, 非对称分布# k. G! y4 O0 w7 y/ Y) H! H1 ~
Asymptotic bias, 渐近偏倚
8 X# f, m C* D6 ZAsymptotic efficiency, 渐近效率 W9 A7 N' y" W* A" E$ ~
Asymptotic variance, 渐近方差/ ^7 U; G! z6 ?- i" M1 N, ~
Attributable risk, 归因危险度1 z5 B: R7 C5 P* O& ~, Z; R
Attribute data, 属性资料4 L# j, \, k4 J- G1 l$ u+ z
Attribution, 属性
& ?+ [) i; i+ L, EAutocorrelation, 自相关7 t( d& t! u: P4 r) c1 `- N
Autocorrelation of residuals, 残差的自相关( y1 Q4 ~' u+ `0 t2 W5 E5 v
Average, 平均数
+ K W+ L: H: M6 a7 V$ D x" e K2 s) FAverage confidence interval length, 平均置信区间长度- c4 ], }9 O. t L9 x9 V) o% b' q
Average growth rate, 平均增长率; G+ O D7 n* C2 f0 L" o/ u
Bar chart, 条形图
1 S8 M( j. _) \/ F9 f" J' iBar graph, 条形图
2 y: z: n" {' c) ?' G1 y5 m+ aBase period, 基期0 j7 r* c2 p/ C+ Y3 _
Bayes' theorem , Bayes定理
" I1 g: l3 z! t. e; m% p& l UBell-shaped curve, 钟形曲线
' B& Q8 g) B% V8 zBernoulli distribution, 伯努力分布
( K( E5 n0 _8 W* a" ABest-trim estimator, 最好切尾估计量
& z* B/ U. U h: P: Q* lBias, 偏性1 ~7 ^$ [- N# I4 F1 e: v* U
Binary logistic regression, 二元逻辑斯蒂回归* u/ f. ?7 b# }8 j2 N% _: N! y
Binomial distribution, 二项分布
. f/ `5 I2 @( S* e' l# y, J9 FBisquare, 双平方7 u7 \, W2 D) d1 N
Bivariate Correlate, 二变量相关4 q- Y0 u7 b9 I& t9 f
Bivariate normal distribution, 双变量正态分布
* K5 r5 g7 u: x! m/ a+ aBivariate normal population, 双变量正态总体* _( s+ V- t' E* y
Biweight interval, 双权区间
" b) K# i( u, N$ t6 D- |8 i5 JBiweight M-estimator, 双权M估计量
9 E) L4 V% y& BBlock, 区组/配伍组
1 {6 Q, J7 f5 b6 f: X/ E3 N! RBMDP(Biomedical computer programs), BMDP统计软件包
4 n7 d6 u+ i; Z: B/ W* J2 @/ kBoxplots, 箱线图/箱尾图
: W/ a3 s8 f9 Q( x N0 _! j8 YBreakdown bound, 崩溃界/崩溃点
: F4 y D8 P$ s# iCanonical correlation, 典型相关" b3 @4 K' j" C$ [4 `
Caption, 纵标目 w. k. F9 S/ e( u: Y) E' U2 B
Case-control study, 病例对照研究
+ o; m/ c% ?, zCategorical variable, 分类变量
$ d# @# E A& J9 l" Q, VCatenary, 悬链线( M* F& `: o8 U
Cauchy distribution, 柯西分布
, n- I& J2 E8 f$ a" F# h& e3 ?. u1 m) u' QCause-and-effect relationship, 因果关系
: K4 q7 n& d3 c2 }8 l7 ~, r- }Cell, 单元& {1 B- w: A% N& B3 l2 K
Censoring, 终检; Y6 y& P& I+ G( M# @* ]9 f
Center of symmetry, 对称中心, l E: M7 k4 U- \& w+ D$ {& {
Centering and scaling, 中心化和定标/ Q5 k- a- w& p5 m! b
Central tendency, 集中趋势
1 a! g/ j& k& A+ bCentral value, 中心值& M# c, z' h/ z
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
, B5 Z! t5 J/ S7 F1 j6 C) oChance, 机遇4 R7 z2 R a, b8 T' W
Chance error, 随机误差7 ? Y" t1 U G p) N: ?7 E
Chance variable, 随机变量
. M- e& ^. ?6 S) FCharacteristic equation, 特征方程7 V# t* e* h1 ]" X' A9 t# j
Characteristic root, 特征根& Y+ |# e# c' n4 @+ ?
Characteristic vector, 特征向量
) }7 w& Q( t4 t2 U* `' AChebshev criterion of fit, 拟合的切比雪夫准则$ P+ l' x3 A7 u+ H' m# N
Chernoff faces, 切尔诺夫脸谱图
2 M& y7 p- r- o, P; UChi-square test, 卡方检验/χ2检验
2 y( i5 }1 x' w& c3 M3 q9 KCholeskey decomposition, 乔洛斯基分解
6 q5 ]" ~, P+ B, c V4 x: aCircle chart, 圆图
, u3 |1 \8 k3 m: }2 O9 B8 RClass interval, 组距
+ }) _ c- X! k" t A6 J3 d4 AClass mid-value, 组中值1 x; n7 d9 }7 Z6 V) g1 N
Class upper limit, 组上限
+ {' x% z) Z9 g; J/ D9 aClassified variable, 分类变量
6 O, I7 I% Z8 E) m' L+ O qCluster analysis, 聚类分析! Z( L4 v% p; r0 r
Cluster sampling, 整群抽样' Z" T0 R' h6 z( O9 ^
Code, 代码
# |6 o# y0 F: z3 n7 l4 G+ uCoded data, 编码数据3 q- @8 O( y7 t/ D* _
Coding, 编码
1 L; ^9 D4 b( b" F0 rCoefficient of contingency, 列联系数% V9 u) f6 `6 K) \
Coefficient of determination, 决定系数
" g9 |- R# d: z4 f; ]- M# BCoefficient of multiple correlation, 多重相关系数( u: O* Y8 M- o) ]& X- W
Coefficient of partial correlation, 偏相关系数
" M$ {. e, c( \0 vCoefficient of production-moment correlation, 积差相关系数9 u: @/ @$ l1 n$ }
Coefficient of rank correlation, 等级相关系数
) U6 T; B1 S+ O, r1 M* K5 tCoefficient of regression, 回归系数. v- e4 @2 i2 u8 x3 {: F, V
Coefficient of skewness, 偏度系数
V2 n b& R$ h3 VCoefficient of variation, 变异系数# {6 f) `& E. h. j& R: N8 @
Cohort study, 队列研究) b' v- ]6 L' I g
Column, 列) X( g( Y1 x. o) U% y
Column effect, 列效应
- @. W Z& ~( BColumn factor, 列因素
& A! K" z* Y& v0 ~& J% mCombination pool, 合并/ r( {* n; p- {! d
Combinative table, 组合表# W8 E, f* Q# ~8 l* X, `( ^* c) z# d
Common factor, 共性因子
1 _8 l' t& W, v" ]) aCommon regression coefficient, 公共回归系数
- e: b8 S/ C7 t5 j$ bCommon value, 共同值& R# A- h6 H7 n3 \, |7 z9 p% Q
Common variance, 公共方差0 J) Q X0 |3 s# n
Common variation, 公共变异
8 ^( Y, \9 e: L3 D0 h1 _Communality variance, 共性方差
! x- d; m9 k( [5 F% ^; GComparability, 可比性
`; {) `) z C BComparison of bathes, 批比较; O0 G% Q+ W8 }# B" G2 i
Comparison value, 比较值& A" R& k( b6 F+ i( y+ m3 a; I
Compartment model, 分部模型 N# p0 n- ~" v
Compassion, 伸缩
l! X' M3 g$ w' DComplement of an event, 补事件3 m I( f: G9 f) e
Complete association, 完全正相关
/ h* Q# i# o! z" L- e gComplete dissociation, 完全不相关
4 ~3 ~0 i6 [" F, GComplete statistics, 完备统计量
/ {' Y' B6 k* t2 uCompletely randomized design, 完全随机化设计
9 }0 W$ Q1 x3 L/ } [+ x* [, _. a6 ?5 W5 {Composite event, 联合事件! A8 ]5 }0 H2 ^0 l' [, ?
Composite events, 复合事件* N& ]) }. u3 X! @1 d" b9 u! e
Concavity, 凹性7 U4 t' A5 w/ G3 F" D0 l
Conditional expectation, 条件期望4 `2 F ^0 `: b
Conditional likelihood, 条件似然
) {. \8 }% I7 b* pConditional probability, 条件概率! T3 D6 O8 C" s N2 M4 q( w! H
Conditionally linear, 依条件线性
6 U0 a1 X, K1 k% F1 `Confidence interval, 置信区间5 \5 a0 R" J$ ^( W
Confidence limit, 置信限
9 b; D9 M" [. GConfidence lower limit, 置信下限
% Q& k; A3 y' L' A4 `3 IConfidence upper limit, 置信上限
) J- z0 @% J3 I; |; RConfirmatory Factor Analysis , 验证性因子分析: o. e4 O5 Q% `" |, [- w+ Y, S
Confirmatory research, 证实性实验研究
* Y3 X, e+ w' A+ X6 \Confounding factor, 混杂因素
+ t# q+ F- w& H' m) tConjoint, 联合分析+ a" O0 a3 a" J, S
Consistency, 相合性3 d) U. D& q& L1 c8 D4 p* [7 E T
Consistency check, 一致性检验# r2 s( E5 d$ P+ A& m6 B
Consistent asymptotically normal estimate, 相合渐近正态估计& Z% @+ I9 n& r
Consistent estimate, 相合估计
8 c: J9 E7 f/ z0 R JConstrained nonlinear regression, 受约束非线性回归
: D- N' a% }% q, H( MConstraint, 约束
; z' V3 V% S% @* I- }Contaminated distribution, 污染分布
' n; r1 C# e7 iContaminated Gausssian, 污染高斯分布- o: ^1 z/ i# U5 l' o( H5 Z
Contaminated normal distribution, 污染正态分布! g6 z8 {/ |- B2 T
Contamination, 污染
* u" b Y- n* u, [2 W7 o" cContamination model, 污染模型
5 J( f7 D) Z5 \: t/ zContingency table, 列联表
+ T' a9 `7 c$ {6 K% V" _$ s1 k* SContour, 边界线
0 K' n+ a" ?2 |+ L7 x) Z. nContribution rate, 贡献率6 t3 X/ C) c6 x' D2 c6 W$ ]
Control, 对照. O7 N2 i q. _3 `' J9 r
Controlled experiments, 对照实验
# u/ G, y: t' UConventional depth, 常规深度
& G4 E) f9 t4 j. |, e4 v5 yConvolution, 卷积
# D/ i. M. J% ]" z+ `; c8 D, jCorrected factor, 校正因子
2 u; [. A2 Y! W; I- x5 Y. |; ~Corrected mean, 校正均值8 B( b8 R T# _4 r$ @
Correction coefficient, 校正系数
* ^' I* L3 L/ y: eCorrectness, 正确性
. Q' h) I+ K6 e: Q3 ?Correlation coefficient, 相关系数/ e, T2 l/ n2 P$ v, Y$ v7 U1 Q
Correlation index, 相关指数6 O# ^" N, `2 m1 s& w; U
Correspondence, 对应
$ j8 b' o& }4 W. H$ h7 H5 i5 VCounting, 计数
' ^. I6 S* E+ O9 D% LCounts, 计数/频数" m7 z. c4 Y6 f, G/ T
Covariance, 协方差. D9 g8 h9 n! Y
Covariant, 共变
5 x- b0 d$ J. h6 W rCox Regression, Cox回归
2 ~0 @$ n4 M2 j. O; @0 pCriteria for fitting, 拟合准则. C3 m* C; v! I4 k3 S& P
Criteria of least squares, 最小二乘准则 L1 h; h8 k' Z, o( z
Critical ratio, 临界比& C7 w6 }/ E) W+ h9 \$ U
Critical region, 拒绝域 l) j0 @7 o6 r# B, ^. u: E
Critical value, 临界值# Y0 U; t& }2 @
Cross-over design, 交叉设计$ |6 v9 T4 R3 Y! A
Cross-section analysis, 横断面分析
1 {* X% ^+ @6 R( N) {- ] ?/ xCross-section survey, 横断面调查
) C) z4 v1 `* D: k% NCrosstabs , 交叉表 + u" z! B8 `( T4 @& Y8 L
Cross-tabulation table, 复合表
, q; {) C/ ^7 }Cube root, 立方根5 Y, Y! ?' l4 q2 t5 A) ~, L
Cumulative distribution function, 分布函数
* g# ?5 M$ M. S/ oCumulative probability, 累计概率
. f! e L( T/ R2 ECurvature, 曲率/弯曲
. v" l9 A1 V; A9 j1 `* [2 O- ^Curvature, 曲率
9 k/ R0 j8 y0 r% J1 s# oCurve fit , 曲线拟和
7 Q; X2 q- Q( C4 M' tCurve fitting, 曲线拟合+ _! f! U7 n) j
Curvilinear regression, 曲线回归. C3 t, k- b% o8 o: v5 a h
Curvilinear relation, 曲线关系
% a+ i4 `) t( [, j a0 qCut-and-try method, 尝试法
5 D0 W, h+ M1 \6 I- Q( }3 {Cycle, 周期
$ u3 O! _ X! _" f: p# _! \& uCyclist, 周期性- m; z. r& e2 q( {# _
D test, D检验
+ C1 F7 U6 x ZData acquisition, 资料收集$ h$ r9 k. J: M! a
Data bank, 数据库
$ E) d8 N- s' zData capacity, 数据容量" U, W3 R3 U( M4 r
Data deficiencies, 数据缺乏
) a1 f$ l! o. A( XData handling, 数据处理. R$ Q- s# q/ g6 b( s
Data manipulation, 数据处理- c. X+ P0 t1 a$ T3 T4 _9 `8 h
Data processing, 数据处理
5 j3 Y3 ~7 ?+ V6 i% ZData reduction, 数据缩减7 a" _5 v5 W0 @: [+ S8 U
Data set, 数据集( f3 O" S. g+ d0 g0 X
Data sources, 数据来源$ R. B _3 Q I5 y' Z) h" Y
Data transformation, 数据变换! D e, l- L. ~7 Z; G& f
Data validity, 数据有效性# \5 a/ ]% i t/ A
Data-in, 数据输入$ q. {5 I* S9 Z! U- z/ B
Data-out, 数据输出) I! D" v$ A* E
Dead time, 停滞期
0 x# b( s& M$ [Degree of freedom, 自由度
# d/ s0 L3 |. S; MDegree of precision, 精密度/ Y: v* H1 Q8 {2 a+ i$ O
Degree of reliability, 可靠性程度% u% @3 v; }& A
Degression, 递减
: t. H1 H' C' gDensity function, 密度函数/ ^0 s9 l7 y2 u+ K# X0 [( u
Density of data points, 数据点的密度# }/ {$ f. x' h; Y: y' Y. _
Dependent variable, 应变量/依变量/因变量, e8 p: Y. T9 D! k) s* s9 f, d
Dependent variable, 因变量
! [" S; Y! d& F4 g* x% \1 NDepth, 深度
. Y ` I( B. uDerivative matrix, 导数矩阵
# z4 B$ i( t j$ R# k* O; i; vDerivative-free methods, 无导数方法+ L& j5 k( m/ n) f4 f2 O }
Design, 设计
0 G4 l2 ?6 R* S/ eDeterminacy, 确定性
4 l& F$ H* W8 l0 \3 iDeterminant, 行列式
3 q+ h6 `; `' f( yDeterminant, 决定因素
e2 l' r% Y0 w4 P3 tDeviation, 离差 A$ A, a, H! u# r4 j
Deviation from average, 离均差
- f; I) J2 z# L, ]& ?" c- qDiagnostic plot, 诊断图% p( X! I2 X$ \) Y0 q
Dichotomous variable, 二分变量
8 `" Q, S8 t. I) |* y: JDifferential equation, 微分方程
+ A, X% n! {0 M& c; hDirect standardization, 直接标准化法' ?* l" I6 T% a [8 h Q2 n
Discrete variable, 离散型变量1 i# F+ W: R+ H- v
DISCRIMINANT, 判断
4 T+ x; C) s( vDiscriminant analysis, 判别分析
6 i8 `& Y# b* p( M& a& a& tDiscriminant coefficient, 判别系数
& x3 b, |2 \2 G4 t& O! \Discriminant function, 判别值% Z9 Z) K5 d+ T! `$ I1 t
Dispersion, 散布/分散度
- s* ]. O8 M3 M. rDisproportional, 不成比例的' [# G* B" J6 P4 {; ~2 r3 Q6 L
Disproportionate sub-class numbers, 不成比例次级组含量
4 R T1 k- E- X3 M+ e4 gDistribution free, 分布无关性/免分布
7 h0 [5 Z' J$ i% VDistribution shape, 分布形状
& h# o6 D$ N' c1 LDistribution-free method, 任意分布法
2 P" n# P- V) }' SDistributive laws, 分配律
9 M; M0 p) M- F( h& vDisturbance, 随机扰动项5 q* Q' U8 J0 O
Dose response curve, 剂量反应曲线
: P a$ m( g; e2 v" HDouble blind method, 双盲法
! \1 u( J" o7 c J5 L. Z6 _* sDouble blind trial, 双盲试验
+ }- E% v# [/ i0 O; b8 Q1 oDouble exponential distribution, 双指数分布5 |9 y3 C' j) r- ~8 n
Double logarithmic, 双对数
# e1 w" j: [( N, K: n v( ~Downward rank, 降秩) x( i8 J' P3 [0 _( b# I
Dual-space plot, 对偶空间图' P' k7 N# J7 Z( V: H
DUD, 无导数方法
- f$ \5 \& }% E& FDuncan's new multiple range method, 新复极差法/Duncan新法
Z$ j$ f* ~* W1 c2 W6 iEffect, 实验效应3 `! {0 d! C2 h' c x, Z
Eigenvalue, 特征值
$ D; g+ q" e$ s$ cEigenvector, 特征向量
) `* v2 ]4 R) S6 c. t' _2 OEllipse, 椭圆
, b5 R7 L( f' A; x+ j) i5 mEmpirical distribution, 经验分布
0 ?% ?( `: {9 O0 pEmpirical probability, 经验概率单位" o- R* Y/ t' }/ _
Enumeration data, 计数资料
) x2 t( l, R' a3 r# v( W5 EEqual sun-class number, 相等次级组含量9 M+ ]2 e& a6 v& N/ b |
Equally likely, 等可能
) s7 n$ O( x4 G* K8 ]( O. o6 ZEquivariance, 同变性# a2 q: j* I0 ~, o* U$ Z; u3 w
Error, 误差/错误
% u/ l; V+ W. F% m0 U& x; jError of estimate, 估计误差
5 S4 H; c; y; Z# B/ w8 k2 C- \7 }4 uError type I, 第一类错误
# K" z6 h! \9 I* S+ j6 L8 NError type II, 第二类错误# c5 a/ C8 r8 f4 Z' @
Estimand, 被估量
5 ?" D8 j6 i0 \5 S( o: s# IEstimated error mean squares, 估计误差均方) ^/ J7 e2 {; R: P5 I1 E
Estimated error sum of squares, 估计误差平方和0 E3 L; B) {: d& ?, S) O0 v( f
Euclidean distance, 欧式距离
* E7 h0 m% a! R8 |Event, 事件* u9 ]- }; m6 I" }0 X
Event, 事件% ]. E' F. R( G# J
Exceptional data point, 异常数据点) s' j2 J Y) h% a& Z2 O3 k
Expectation plane, 期望平面7 I& {" d, F! b; W" I
Expectation surface, 期望曲面
! c6 |( Y c/ oExpected values, 期望值
) ]/ W' m' R5 f) C% p( ?% [Experiment, 实验
6 [: @& x- Y+ c9 x' c; F! ]9 O- eExperimental sampling, 试验抽样. U( H6 e2 e/ l' }
Experimental unit, 试验单位
( v7 [" L& N2 b5 G# \7 G! S2 L: IExplanatory variable, 说明变量5 K2 g; s% l9 P6 o0 g
Exploratory data analysis, 探索性数据分析
# c$ d3 G' _: O# B1 U# KExplore Summarize, 探索-摘要
$ Z' ?% A5 n* L' i2 R2 {Exponential curve, 指数曲线, z+ i0 a% \2 V( S5 I- {, V5 h
Exponential growth, 指数式增长, d6 X& f6 i$ o' d0 C4 k' b
EXSMOOTH, 指数平滑方法
3 Y; s# {& ^3 hExtended fit, 扩充拟合
5 T% j& Q" o5 h: I. q; UExtra parameter, 附加参数" D7 K7 s7 q# ^- G
Extrapolation, 外推法
$ d6 }: H/ ?; ]& W8 GExtreme observation, 末端观测值$ S4 n& d4 w; c9 W: F/ [+ X% o
Extremes, 极端值/极值
, q9 U$ g3 G2 k# ~+ dF distribution, F分布4 h9 b3 Q* J) a4 b
F test, F检验
8 Z5 H4 ?6 s- m9 Q: S% sFactor, 因素/因子
) E. S+ h+ h, E% u" vFactor analysis, 因子分析" i0 }* g7 p6 X/ \
Factor Analysis, 因子分析
( P& E& i5 L* l# M$ p5 Q& I# QFactor score, 因子得分 8 W6 a5 x% a# W6 m6 k4 V
Factorial, 阶乘# h; y4 i- O, |
Factorial design, 析因试验设计5 \! i( Z. y5 d' _
False negative, 假阴性
8 K* n# M. P7 c- r/ fFalse negative error, 假阴性错误7 W T: V$ V4 U& r, M
Family of distributions, 分布族
' S+ h3 T1 l: G% g+ GFamily of estimators, 估计量族6 x4 y( R$ I8 G
Fanning, 扇面
1 }8 V$ K" N8 zFatality rate, 病死率7 p: P* b: l" Q0 N. r' ]
Field investigation, 现场调查0 y/ N! d/ }; N/ I3 a j1 k+ T2 I
Field survey, 现场调查
" M% P. ~( p; z5 M: m8 p/ w- Z- _Finite population, 有限总体
* O3 \5 u# z3 J8 s z k) nFinite-sample, 有限样本
% {+ `- G2 t9 F: ?0 \First derivative, 一阶导数
& h( `6 Q; q! r/ ~9 S E1 @( l* @First principal component, 第一主成分" g& N2 }5 G& o8 }& Y. a: e
First quartile, 第一四分位数
. a3 `! E" F2 L2 ~. PFisher information, 费雪信息量6 Q) }# k$ _: J
Fitted value, 拟合值
3 e6 \# |0 L- L+ d, f7 U9 tFitting a curve, 曲线拟合0 q5 u! j' f! l! r2 K/ u: @. t# V
Fixed base, 定基% F \& K. } @) n4 I7 C% @
Fluctuation, 随机起伏
0 @/ |3 E; f+ L9 W0 G% ?Forecast, 预测
4 y, M) k$ X x) SFour fold table, 四格表. B* s0 S; b# S! u
Fourth, 四分点
c9 V: w) M. f' Q. @Fraction blow, 左侧比率1 z6 f! I% v I+ r s
Fractional error, 相对误差
3 s) @2 K( O* `( R g3 O5 c$ p6 W5 f# aFrequency, 频率7 H9 H6 H! P2 E* L9 U2 x5 u" {& [
Frequency polygon, 频数多边图) w7 Y3 }- Z: i
Frontier point, 界限点
. _. ^6 i5 i/ k8 f' e8 G7 S NFunction relationship, 泛函关系: F. F3 z4 G7 I
Gamma distribution, 伽玛分布
$ \( _% d& T( }: ?% QGauss increment, 高斯增量" Y, U6 r# y( E
Gaussian distribution, 高斯分布/正态分布# W5 X+ R+ G+ _% E' d
Gauss-Newton increment, 高斯-牛顿增量' @" d! {' B0 k: j2 z$ K4 m
General census, 全面普查8 s1 |; f! i8 j+ @
GENLOG (Generalized liner models), 广义线性模型
V7 o! s) _6 O3 Q' KGeometric mean, 几何平均数
5 Q' i$ k1 V; V. T7 ?: VGini's mean difference, 基尼均差9 U- x) Z* |" X
GLM (General liner models), 一般线性模型 . z3 L$ E* N2 U2 Y5 F0 m
Goodness of fit, 拟和优度/配合度
6 M) M9 N3 \+ \1 y- FGradient of determinant, 行列式的梯度
7 g, ]; A9 h4 n+ U) U0 vGraeco-Latin square, 希腊拉丁方
/ p; f# c& t$ ]) kGrand mean, 总均值6 ^$ D; m; y- [& g
Gross errors, 重大错误& R- t2 F' P! y5 Y) x% d
Gross-error sensitivity, 大错敏感度
' {7 Q P ~ j8 d, \, F$ nGroup averages, 分组平均4 ^1 f/ f' w8 e; X
Grouped data, 分组资料
- D9 G7 V! u# ^2 j+ Y3 O gGuessed mean, 假定平均数
2 [, z1 H u- Y" Q1 {Half-life, 半衰期" n0 [1 u* t& `. m' c
Hampel M-estimators, 汉佩尔M估计量' N8 l4 p0 G9 e
Happenstance, 偶然事件5 R4 b# v) e: K
Harmonic mean, 调和均数! w* Z4 I2 F0 E R
Hazard function, 风险均数9 f( U% M: H8 I6 Q
Hazard rate, 风险率
0 p: p9 d6 ~' DHeading, 标目 ' V" m- f* m3 d# T2 N
Heavy-tailed distribution, 重尾分布
- X; g7 n0 @$ f* CHessian array, 海森立体阵( N3 P( H+ S5 c/ O; E
Heterogeneity, 不同质6 @6 q0 h6 a3 z, [. y* u: V1 @
Heterogeneity of variance, 方差不齐 0 j$ n) A" c% Q, Z4 H9 T- P
Hierarchical classification, 组内分组9 b b6 K9 ]4 h
Hierarchical clustering method, 系统聚类法$ n$ y/ |9 ^$ B6 n* {7 b
High-leverage point, 高杠杆率点1 ]2 A, m$ q$ _! Y, z
HILOGLINEAR, 多维列联表的层次对数线性模型+ c" w: e D. A3 s
Hinge, 折叶点
T o5 P* d; T( i% |. ^9 `( U& _1 ?" kHistogram, 直方图
- r# j1 \! ]& x; ^- bHistorical cohort study, 历史性队列研究 % f7 e. i- O8 \3 z) }, J& E0 q5 Z
Holes, 空洞) [ ?9 P M" i" |8 m
HOMALS, 多重响应分析
5 R: y( V/ i7 u0 Q/ yHomogeneity of variance, 方差齐性! d4 D7 D) k9 G0 F a
Homogeneity test, 齐性检验% D+ ?2 k% T, }2 P: @4 y
Huber M-estimators, 休伯M估计量. v; x1 {' W v6 i( Y9 N
Hyperbola, 双曲线
- t2 X7 i1 V% o# G4 xHypothesis testing, 假设检验
. R. Y8 f5 {7 l) \$ Q; AHypothetical universe, 假设总体
6 {, |2 Y, I6 z8 _ DImpossible event, 不可能事件% S4 [& ~+ g6 f& i
Independence, 独立性
2 Z4 y ?: W- A+ z( iIndependent variable, 自变量
. K* m! }7 @" J4 m1 n4 A, GIndex, 指标/指数
. j5 @, \% _7 E3 B' iIndirect standardization, 间接标准化法/ k$ j- D" {4 {$ d! U
Individual, 个体; n9 A5 a' Y! e- M
Inference band, 推断带/ l8 {+ F" z( W" X. ~4 p, u
Infinite population, 无限总体
, a$ U5 F! x: [4 g7 H) B* J0 SInfinitely great, 无穷大
: H' ~& Q# b r9 ^. x' E- D6 K" FInfinitely small, 无穷小
: N' I0 `3 Y: x# F; D& H# y6 ~Influence curve, 影响曲线% Q6 T( l# E/ p$ y! Z- J0 {
Information capacity, 信息容量
) `. F+ I6 ]# x3 O4 l- @3 xInitial condition, 初始条件" O+ S# G/ H% \1 m
Initial estimate, 初始估计值
1 g2 N* c$ U3 \ {Initial level, 最初水平
* u( V7 h$ A5 [/ _8 N7 J6 \8 yInteraction, 交互作用, w6 R% M+ A6 `
Interaction terms, 交互作用项
- _0 a; K- ^6 i" XIntercept, 截距
* o# |1 H" U0 Q4 U. Q+ KInterpolation, 内插法9 A m# ~3 I9 K6 y0 u8 A' q, Z5 N5 t
Interquartile range, 四分位距
7 I) c' l- K6 m" f# @4 hInterval estimation, 区间估计7 E# p. k+ r; a' D! T0 u8 ~: y
Intervals of equal probability, 等概率区间7 e# i3 ?6 F, }- [1 @1 T
Intrinsic curvature, 固有曲率
, R0 r9 n! c8 w- W2 |Invariance, 不变性
( a: Z3 `% S" N2 m2 |% ^Inverse matrix, 逆矩阵
$ ~( f6 d# V* | A& j) G$ z. x" [Inverse probability, 逆概率
& m2 F1 k+ {* W" p) l% n' jInverse sine transformation, 反正弦变换
4 o- K4 o0 U1 s' W" d: NIteration, 迭代
% ^/ }6 A0 I( {% O c7 \; h0 h; BJacobian determinant, 雅可比行列式
D; I" l) H# P% {1 HJoint distribution function, 分布函数& G s- V0 I0 |- C
Joint probability, 联合概率$ @/ B' ?" b: v
Joint probability distribution, 联合概率分布
1 A# N. q$ @4 D# ?2 m1 H. FK means method, 逐步聚类法
8 |+ k t: e0 GKaplan-Meier, 评估事件的时间长度
% |8 ?7 l' a, `% Y- P ?Kaplan-Merier chart, Kaplan-Merier图
4 H% d9 } S* qKendall's rank correlation, Kendall等级相关
4 z. e9 t- Y3 o; @2 a1 \4 SKinetic, 动力学
1 J( x; ]7 G/ r" E- N! fKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验' i7 y2 x8 F7 M+ D' I
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验3 w- s, B: m; D1 L3 A
Kurtosis, 峰度
+ f" V1 D* T" @. S9 b: MLack of fit, 失拟% v, b2 Y8 U# x$ H {
Ladder of powers, 幂阶梯
' o( e! N! D" Q7 RLag, 滞后
9 V: ^ I, C4 @0 {- eLarge sample, 大样本. e4 @8 D" Z7 a- N
Large sample test, 大样本检验
, R% t) H$ [9 Z: X4 |; _! j9 t, NLatin square, 拉丁方
- s* f, ]3 q3 J" [8 M. S* sLatin square design, 拉丁方设计9 y6 F- l; H* z; l
Leakage, 泄漏- D1 ?& { t4 t# i( g' k' J
Least favorable configuration, 最不利构形6 J. ?6 {6 r4 d9 [. i& Y7 \
Least favorable distribution, 最不利分布
) k+ {( \' ^# W: C+ G& V% H" TLeast significant difference, 最小显著差法5 z9 v; O5 l' r, |
Least square method, 最小二乘法4 B8 Q+ p% |- m7 }' G6 }
Least-absolute-residuals estimates, 最小绝对残差估计/ k# T; b6 Y0 E3 q
Least-absolute-residuals fit, 最小绝对残差拟合# i& O5 P3 q [; t) B, s
Least-absolute-residuals line, 最小绝对残差线
i$ R" T% j& [6 U( ELegend, 图例- W, p8 `# ]# g/ U& c# K
L-estimator, L估计量4 g! Z. g( b: B1 D% j
L-estimator of location, 位置L估计量
; e. d) e3 ~0 N) kL-estimator of scale, 尺度L估计量
) `; X% p& ^( s5 z* }3 I2 l2 PLevel, 水平
, t P* s3 u% I+ Q" g" RLife expectance, 预期期望寿命
* Y; o" {+ H+ n2 ~% U6 cLife table, 寿命表8 m2 W; P" s7 K# n0 T0 b
Life table method, 生命表法6 W% V1 a% w0 E I) c3 }
Light-tailed distribution, 轻尾分布
' l& [$ S9 m! m# F* jLikelihood function, 似然函数( s' B% U- R' T! h* }/ f9 u! U
Likelihood ratio, 似然比
( X& R. m7 C/ E0 f4 n: _2 Lline graph, 线图
8 y i; Y ?* X0 G' q, wLinear correlation, 直线相关1 X1 B. y" ~8 Y
Linear equation, 线性方程: L" w) [3 b9 E4 I) j2 c$ F
Linear programming, 线性规划: E( H/ M/ Q# U" g% o, c
Linear regression, 直线回归
6 P+ ?' t! E! B% ILinear Regression, 线性回归 x6 i7 l( t& q0 M% C
Linear trend, 线性趋势
5 _, n; y* a2 X0 n- G0 MLoading, 载荷 + I1 G6 \' m i4 ^7 z6 f- U) w
Location and scale equivariance, 位置尺度同变性
" t7 ^ v% w$ n F; U0 K$ C( SLocation equivariance, 位置同变性/ y' }+ K: S5 R" [2 x* i ^
Location invariance, 位置不变性+ E" ^0 n- J: B1 g" P
Location scale family, 位置尺度族
5 i$ {4 @/ q$ i$ n: F5 ALog rank test, 时序检验
) X" n3 k7 K2 mLogarithmic curve, 对数曲线
6 d. s I( }2 \" I, FLogarithmic normal distribution, 对数正态分布) z+ c5 Q5 [. G: T
Logarithmic scale, 对数尺度
4 H o% K* P5 ^/ N KLogarithmic transformation, 对数变换
# J e* v" Q; _Logic check, 逻辑检查
9 l2 c: G- F$ v# j( J. n% hLogistic distribution, 逻辑斯特分布2 y& i/ X* Z7 V, }2 P$ n0 T
Logit transformation, Logit转换. M1 z8 n( d. d; b: v6 ^! s
LOGLINEAR, 多维列联表通用模型
; `+ V' k; H5 w6 O4 W' M1 hLognormal distribution, 对数正态分布8 f3 b# I' v U
Lost function, 损失函数3 B* t; }, Z6 J$ x+ O
Low correlation, 低度相关' K$ _( I; A$ D5 ~
Lower limit, 下限
7 U, S) B* i$ F6 T$ J7 o. PLowest-attained variance, 最小可达方差5 b! h- o* O8 E5 j* C. X
LSD, 最小显著差法的简称! ?) k- H! u: |# k, q* |1 y& X
Lurking variable, 潜在变量2 o: ~( N% _$ Z0 I) o
Main effect, 主效应( ]* {/ d- s4 m2 @# W3 }7 D/ {
Major heading, 主辞标目
% a6 b8 |0 H3 b/ F. r. bMarginal density function, 边缘密度函数! E. @5 x8 E0 c P. Y
Marginal probability, 边缘概率
4 y: l/ y; Y6 y" c& `. r) YMarginal probability distribution, 边缘概率分布
8 R6 a- v" c5 d" E5 m9 R, VMatched data, 配对资料* [2 s7 l# N# \* d7 [
Matched distribution, 匹配过分布
. O# x: w/ Q; ]; UMatching of distribution, 分布的匹配
3 w; I" _# F7 cMatching of transformation, 变换的匹配
' C l0 ^3 l' N8 nMathematical expectation, 数学期望, v$ a" _2 J6 s! O x
Mathematical model, 数学模型
: `# K# S$ L Z% \' j' qMaximum L-estimator, 极大极小L 估计量; H$ f$ J' G1 Q2 B6 Q4 ?9 P
Maximum likelihood method, 最大似然法
' \; N* h9 b& S! }$ \5 Y4 SMean, 均数, ?* \+ t: q8 |4 b7 \ J* Q
Mean squares between groups, 组间均方% m* z7 ^" r N. ^, d% r F
Mean squares within group, 组内均方
- e5 O g5 K, XMeans (Compare means), 均值-均值比较& w0 I9 l6 c9 _: e/ V
Median, 中位数3 B/ Z' X) G( ?: g+ u: A; h, U
Median effective dose, 半数效量8 [9 S& N8 ^7 N/ A
Median lethal dose, 半数致死量, _6 A9 e7 |4 J; K
Median polish, 中位数平滑, r6 U$ h) [/ u k% L) [% f; X: C
Median test, 中位数检验# b, R& H0 j( q3 a5 b2 M) w. J& {1 v
Minimal sufficient statistic, 最小充分统计量9 ~8 z% L/ y2 D- w) w. I3 w
Minimum distance estimation, 最小距离估计7 Z7 U, {* M1 @& c y
Minimum effective dose, 最小有效量
. O9 k8 p: D) \- F7 t5 a CMinimum lethal dose, 最小致死量
, J2 |3 r) \) ]& G( m" c* L# EMinimum variance estimator, 最小方差估计量* X7 }1 F- a2 l
MINITAB, 统计软件包
, ~8 U6 \, Y9 NMinor heading, 宾词标目
8 H: g3 Y5 s1 a* H5 f9 B( @$ x/ G, ~. nMissing data, 缺失值8 D$ D* P4 S8 U( P; y! R9 R
Model specification, 模型的确定! \8 S4 y" x" j) X) y5 n
Modeling Statistics , 模型统计1 O" o1 A$ M) l6 ?
Models for outliers, 离群值模型3 R4 d/ U: d$ E' x8 G
Modifying the model, 模型的修正2 I' W, s Q; A% I8 s. S1 n
Modulus of continuity, 连续性模
2 U$ _' e% X4 |( a1 FMorbidity, 发病率 W/ d0 D9 H9 R
Most favorable configuration, 最有利构形
. |- W9 @( v. C; J9 mMultidimensional Scaling (ASCAL), 多维尺度/多维标度 S8 N, [" d* M( j; d0 {3 h
Multinomial Logistic Regression , 多项逻辑斯蒂回归, s4 V/ {! `% G8 w& }2 `
Multiple comparison, 多重比较
' g1 T( |! F. k. LMultiple correlation , 复相关
3 j! y* s$ E4 e v, ~! SMultiple covariance, 多元协方差% Y8 o/ Z3 ]* w/ S8 \0 \# _5 ^0 w: l
Multiple linear regression, 多元线性回归
/ { W& D7 y5 oMultiple response , 多重选项
/ A% J; `2 j3 ~: n2 j- u0 wMultiple solutions, 多解9 Y5 p. [+ |; ~# [9 A
Multiplication theorem, 乘法定理- k0 I7 G% t/ q( p( ~
Multiresponse, 多元响应0 F, U( ?$ c* l3 _
Multi-stage sampling, 多阶段抽样1 {! T6 N* e/ ?
Multivariate T distribution, 多元T分布" x8 _4 G2 L: L6 V- m* _: Q7 o; d
Mutual exclusive, 互不相容$ ?) V3 |$ r) h" |' X
Mutual independence, 互相独立" M% @( W9 z7 f. T' R- X; r" g
Natural boundary, 自然边界' x3 k6 Z ~) }
Natural dead, 自然死亡* `8 N; q% g, b7 i
Natural zero, 自然零
+ P' k5 c' x, E6 h0 s4 w" N/ U6 m* vNegative correlation, 负相关
; h2 S- S; [ ^; A% N! `Negative linear correlation, 负线性相关
0 Y0 e _2 Z3 b4 PNegatively skewed, 负偏
/ o0 X) X0 K5 v2 I j: SNewman-Keuls method, q检验5 d3 I O: I# C
NK method, q检验
7 O6 Y( b0 T* TNo statistical significance, 无统计意义7 T9 J- r7 K4 x* {0 \( `: d
Nominal variable, 名义变量
& D! r* S2 I0 V' q& @7 nNonconstancy of variability, 变异的非定常性, K, \0 P; l; F: G. E- f
Nonlinear regression, 非线性相关
1 s( U; q' l) W4 C' CNonparametric statistics, 非参数统计
1 E' g2 l1 b; n% o& |" L! z* sNonparametric test, 非参数检验7 e- u6 K5 q$ E Y/ w
Nonparametric tests, 非参数检验
1 T- }3 r% O$ I, p& B$ INormal deviate, 正态离差' S& y$ n* m7 R: a2 A
Normal distribution, 正态分布, u8 P4 L9 Q6 v( ^5 b/ E% X( q
Normal equation, 正规方程组; @+ T/ E& M! n: H4 H7 w; q/ Q
Normal ranges, 正常范围; \5 G4 N% q% m$ Q8 G6 \
Normal value, 正常值
0 \9 u1 ?3 A7 b/ ]' O" B- r' lNuisance parameter, 多余参数/讨厌参数
7 ^) x; W/ F5 qNull hypothesis, 无效假设 , [# ~0 }/ f( N6 [" Q
Numerical variable, 数值变量
( O/ ]0 }/ e$ y2 RObjective function, 目标函数- ]' z8 G+ v- W
Observation unit, 观察单位
7 d. ` T! \" M8 W0 ]Observed value, 观察值; T: Q" h; j- [" C
One sided test, 单侧检验. y0 n; J6 _! B
One-way analysis of variance, 单因素方差分析8 ]* X" D7 ?7 g& M1 I
Oneway ANOVA , 单因素方差分析4 W% c7 m, g* s# `5 f3 r" W* F* n
Open sequential trial, 开放型序贯设计7 I7 k4 V$ ^+ k! V+ C+ O2 P7 C
Optrim, 优切尾
( S# w9 M% T) @* EOptrim efficiency, 优切尾效率
% x* R! w. Q+ [% U! V6 XOrder statistics, 顺序统计量
8 a- k+ s, {; _0 k# S# D$ _: EOrdered categories, 有序分类
4 o# A$ k" Q+ `Ordinal logistic regression , 序数逻辑斯蒂回归! L. I) o1 T! j* v0 c. B
Ordinal variable, 有序变量
- n, r i2 N' `Orthogonal basis, 正交基3 I3 {( j) _0 e
Orthogonal design, 正交试验设计
. u) n, o- w. GOrthogonality conditions, 正交条件
" P2 ?+ n8 ~7 C% ~8 tORTHOPLAN, 正交设计 ( e3 a6 L! T; K u5 I, n
Outlier cutoffs, 离群值截断点
1 C% x: B$ c2 w7 J: U9 JOutliers, 极端值
( O" G2 @, ?; r, t: ]% COVERALS , 多组变量的非线性正规相关 O2 s% u; f" }/ K3 @, c! b
Overshoot, 迭代过度
) m4 h+ h4 _ p% bPaired design, 配对设计3 Z" k8 u+ ]9 D+ Z) ?
Paired sample, 配对样本1 Z4 q( ~3 j$ o' [8 @/ C" g
Pairwise slopes, 成对斜率
; e, e5 n7 D+ s) }- j/ V7 aParabola, 抛物线$ z2 c0 C5 a3 M& i0 u0 w# L
Parallel tests, 平行试验
]* Q" ^# {3 `Parameter, 参数, m& W, B' a, ~' }
Parametric statistics, 参数统计
% a$ S6 W* P! SParametric test, 参数检验
4 q0 T+ d# {9 \! R CPartial correlation, 偏相关9 F6 k- w6 m+ i- s2 C" V, U
Partial regression, 偏回归$ _+ c9 k/ t4 m% a
Partial sorting, 偏排序1 i3 Y4 F7 v; c
Partials residuals, 偏残差
, B5 v: ]: W s0 WPattern, 模式7 v: `# m9 Z; T' r
Pearson curves, 皮尔逊曲线
$ [& x. x6 H9 H2 L: |, e- W! YPeeling, 退层, ~: p+ c+ `( C( R
Percent bar graph, 百分条形图2 F4 R* F6 i' T& g- E0 ]
Percentage, 百分比
t+ k0 T; S4 E9 XPercentile, 百分位数/ c8 j6 I w e0 s
Percentile curves, 百分位曲线' }1 U4 D) U. ]; J; l
Periodicity, 周期性, v x8 E! x$ F$ c- r
Permutation, 排列. o8 P9 g" |* M2 B
P-estimator, P估计量
7 Y* q b6 w& q& XPie graph, 饼图
* m1 P1 n' H mPitman estimator, 皮特曼估计量
& w" K4 b9 C" f% B; ~, _- {Pivot, 枢轴量
, [ V3 }9 _; K4 ZPlanar, 平坦; ?/ Y; b7 E& B5 h
Planar assumption, 平面的假设
" k. I7 C# K$ B }, i- l! h6 hPLANCARDS, 生成试验的计划卡! B% F( b9 v/ S7 m/ V9 `
Point estimation, 点估计
) z" ?+ U' q% P' mPoisson distribution, 泊松分布
$ I0 V5 I7 V, _ F! Z* _0 q9 \Polishing, 平滑
, V0 F5 F1 e7 Y Y3 _% F( I0 j8 mPolled standard deviation, 合并标准差
5 {. I# a( K3 E# n2 R' h4 iPolled variance, 合并方差
) r5 z; N$ w3 ^; R" }Polygon, 多边图
2 `( y ?+ H* rPolynomial, 多项式; M% l, |3 J0 r: N& G' ~
Polynomial curve, 多项式曲线
1 k9 w4 Q+ z1 ~. `( d1 d6 jPopulation, 总体" T! b7 I2 e7 s2 T" e
Population attributable risk, 人群归因危险度
1 A6 D W# _5 `- N4 TPositive correlation, 正相关
7 p0 e: D9 d* F( b& XPositively skewed, 正偏: Q# ]' Y: h. A1 O, a
Posterior distribution, 后验分布- b' U3 e# H* |1 t! R0 S) c
Power of a test, 检验效能
( B8 ?" f9 y; y5 FPrecision, 精密度8 a' N8 G0 t8 \( [- d9 G
Predicted value, 预测值
$ `: ~5 b# f5 n) e- u6 t- |# RPreliminary analysis, 预备性分析
6 z1 Y" k: z# `; B+ A0 U/ Y1 `9 NPrincipal component analysis, 主成分分析3 Y( p: m1 l4 D" {
Prior distribution, 先验分布
- A; Y" y7 _9 W) j4 p9 {Prior probability, 先验概率- @& m- ?& D9 s" n$ a
Probabilistic model, 概率模型
4 w1 ~) q% D1 Y. d9 d K2 ^! cprobability, 概率
- P3 A7 H" G- G. MProbability density, 概率密度
. Z" F& T: z- o7 O* r) d/ `Product moment, 乘积矩/协方差
7 E& z; Y9 C$ s* W1 ?' _! mProfile trace, 截面迹图# X1 d2 Y5 }' ]+ k1 f
Proportion, 比/构成比
0 G8 s. h" X5 |! GProportion allocation in stratified random sampling, 按比例分层随机抽样
6 v1 I3 D* H$ }- k3 z* ~5 fProportionate, 成比例
" Q% Y0 x+ D) e! v8 o! ]! _Proportionate sub-class numbers, 成比例次级组含量
: Y, Y* q, @. S- u, g! yProspective study, 前瞻性调查
5 v) d* K# [$ C) Q6 p, UProximities, 亲近性 + r- [4 \9 Q; z! \ X% k
Pseudo F test, 近似F检验
: ~% f, B9 r7 D$ ]) l3 q% \Pseudo model, 近似模型/ Z- m/ ]# Y6 u& w( ^! u" ?0 w
Pseudosigma, 伪标准差
$ x r( u& {' u4 }Purposive sampling, 有目的抽样5 ^0 e% c1 m# P4 p+ T, i" p% H9 q
QR decomposition, QR分解3 D" M9 a2 e9 m, Y/ l3 m! @; a, i
Quadratic approximation, 二次近似
) }$ H8 }0 h( M& U/ Y- j# QQualitative classification, 属性分类. A$ @# C. ^& O- g" H
Qualitative method, 定性方法
+ b/ j! z o# z" o/ G2 I. rQuantile-quantile plot, 分位数-分位数图/Q-Q图
0 W0 x+ K3 m, |Quantitative analysis, 定量分析* n) Y+ W `8 h6 }' m4 `
Quartile, 四分位数0 Z4 b1 g" t5 i) I( Q
Quick Cluster, 快速聚类- G9 U0 C8 N* a" S5 O/ o
Radix sort, 基数排序' E# r1 i6 g3 C6 r. M
Random allocation, 随机化分组; }- ]4 |# V9 j
Random blocks design, 随机区组设计
5 @- M# `. m- F1 \+ B- [Random event, 随机事件
- c( a2 ?: w- Y% c/ BRandomization, 随机化3 x" n! s6 `! R5 B" X6 Y$ u
Range, 极差/全距
" @3 n( k( }8 z5 m5 f6 WRank correlation, 等级相关, ?5 ^5 K: ?. q9 k5 |8 U+ q
Rank sum test, 秩和检验( X8 i" I/ D' n2 {; b
Rank test, 秩检验8 ?1 F! g9 s: D
Ranked data, 等级资料: d5 y' O% C. L ]# W) r% q
Rate, 比率1 G9 H9 b; I+ _$ D2 h/ E
Ratio, 比例
5 m! J. r' c8 f9 ?2 O+ J! l! |Raw data, 原始资料
+ g: q; b% ]0 h) R5 TRaw residual, 原始残差, X1 q$ ^$ b D5 B# z0 |( n( H; l; `
Rayleigh's test, 雷氏检验
: T% I& |% f- C" c4 lRayleigh's Z, 雷氏Z值 2 G0 A: r) ?$ ~0 s% }
Reciprocal, 倒数% Q, j' T! l, ~8 j
Reciprocal transformation, 倒数变换7 U' j7 }: d) }" o/ Z/ z N
Recording, 记录8 x8 }+ [7 P9 A- I6 _4 z
Redescending estimators, 回降估计量( ]5 L, w6 {2 D, p( x
Reducing dimensions, 降维
0 a4 e6 }- v7 b/ Z2 `Re-expression, 重新表达# y$ r2 c( n$ }! r/ U% h
Reference set, 标准组; k* T- u# |0 K& k4 j# g
Region of acceptance, 接受域/ Z' D* [& W- M. K; z" w1 R: @
Regression coefficient, 回归系数
* y, E1 s% a/ ~8 dRegression sum of square, 回归平方和8 T4 f# F, c- I* Q: R% ]8 C; h
Rejection point, 拒绝点
- }8 j2 R: g8 E- }" |Relative dispersion, 相对离散度8 k3 q0 ?2 U+ e0 R: t% Z
Relative number, 相对数
; R2 `5 N* B, |1 f; FReliability, 可靠性
, B: G$ i* H% k% R. u, ]Reparametrization, 重新设置参数
" I5 X4 R+ U* c$ o2 c/ X6 XReplication, 重复
. {% L* Y: E: n4 I" H2 {Report Summaries, 报告摘要
U# I m) f3 z; ~* DResidual sum of square, 剩余平方和
; U4 h+ D' s& u# f' _8 Z ^Resistance, 耐抗性
- K9 b$ n- X* D* H4 lResistant line, 耐抗线$ J( q# y( b& v! c
Resistant technique, 耐抗技术 \* }' n1 O' z$ x4 t* n
R-estimator of location, 位置R估计量
7 g6 c: e6 `: S- MR-estimator of scale, 尺度R估计量
" R" c1 Z2 h" }- Z( [, dRetrospective study, 回顾性调查# e% T+ f3 {8 ]; B$ z! [
Ridge trace, 岭迹) \$ Z, |. v3 |# b
Ridit analysis, Ridit分析" d c Y; u. x8 M' K. E
Rotation, 旋转
" R* g8 C1 I& a; R. d P; f( q# D" H: K1 xRounding, 舍入. b8 ?9 Q6 I* F; n
Row, 行; Z& B' B9 E& c" r8 F' Y+ m
Row effects, 行效应 K( h# t: T2 b# o4 ^9 ~% x) K
Row factor, 行因素0 _+ ?+ S3 ]; x; f/ {% h8 Z& F
RXC table, RXC表
k- Q6 T1 _. v6 LSample, 样本
% S7 R v. R5 W% x RSample regression coefficient, 样本回归系数
0 a, V( R$ d ?8 W( O2 j8 vSample size, 样本量9 ?) S9 D5 L! m- P: d
Sample standard deviation, 样本标准差
9 z& J- c- ^' { Q2 P1 p1 s! kSampling error, 抽样误差 A- z, b( J4 n y& `( M7 t+ r
SAS(Statistical analysis system ), SAS统计软件包
- P3 P9 J' w9 x9 PScale, 尺度/量表7 @$ c! B) r, d1 e
Scatter diagram, 散点图
6 s. @5 z* {8 ^6 P; m `4 ISchematic plot, 示意图/简图
$ \' ]8 V' Q9 a: }5 S9 Q7 k: CScore test, 计分检验
. ]# L) e2 K/ n9 h2 M% ?3 ?Screening, 筛检
1 o# ?' P6 B: d, r) m. XSEASON, 季节分析
- e% M: d. z( P5 \3 Q5 e% mSecond derivative, 二阶导数
5 W5 Y: ?+ k, L* R- ESecond principal component, 第二主成分8 w- p! @" T6 O: u) `$ E
SEM (Structural equation modeling), 结构化方程模型 0 N2 ?7 r9 V- c6 x, ~% _
Semi-logarithmic graph, 半对数图/ |5 F7 j0 M( @3 Z& p
Semi-logarithmic paper, 半对数格纸) c) t& D( E$ z8 v% q
Sensitivity curve, 敏感度曲线6 r j' E5 X: E0 G7 W
Sequential analysis, 贯序分析
6 o, T0 ]; r3 LSequential data set, 顺序数据集
' i [$ X" J- o3 y2 V* X, D" _; ISequential design, 贯序设计* a( @- _: y, F- a. W) p
Sequential method, 贯序法) m# S* N3 C# K r
Sequential test, 贯序检验法
6 d2 l2 |; F/ N, a0 T- ?& BSerial tests, 系列试验
4 J7 a" k" R1 xShort-cut method, 简捷法
. m! f. a9 e/ B* K$ {Sigmoid curve, S形曲线: G' z9 V# l) r; g2 _. j$ }5 q
Sign function, 正负号函数
8 F" {9 Y/ ]# }. C; ySign test, 符号检验& z. f& C7 ]/ D. B) o
Signed rank, 符号秩
% @2 g' R8 h$ F8 PSignificance test, 显著性检验
; v+ V* g5 C Y0 I0 B+ rSignificant figure, 有效数字
; S. {4 k5 }& u2 M5 h1 W; gSimple cluster sampling, 简单整群抽样. ]( k. c- ~9 S' e4 N3 x
Simple correlation, 简单相关+ a( O: c' L3 @3 b" ?
Simple random sampling, 简单随机抽样( }' X) t5 s7 j2 ?6 ^1 U/ `
Simple regression, 简单回归+ K- n; g$ x6 Q
simple table, 简单表
6 w- T7 [' G- R" iSine estimator, 正弦估计量
6 e' S" B2 {7 M9 uSingle-valued estimate, 单值估计
9 F+ p X' Q5 `+ u2 {5 X( WSingular matrix, 奇异矩阵6 E" C: S5 k; G# f! y
Skewed distribution, 偏斜分布4 L& r7 V" V. E. e, r' {
Skewness, 偏度/ ^# }8 l+ Z [9 i
Slash distribution, 斜线分布, x2 a! N4 U. r. t2 e1 L0 H; Y
Slope, 斜率
) k7 Y" ~* t8 E& s( M; K6 d2 sSmirnov test, 斯米尔诺夫检验
: W( l: }5 g1 x1 @& ]Source of variation, 变异来源
' f! |6 W8 W. J: ^" V* ISpearman rank correlation, 斯皮尔曼等级相关1 Z6 t7 H+ j2 m0 [
Specific factor, 特殊因子/ Y9 _! k ]9 G& a7 t8 ?) w2 Z
Specific factor variance, 特殊因子方差
( b, X0 U' m6 @Spectra , 频谱
1 N8 j% g# c& I8 xSpherical distribution, 球型正态分布
# {4 k/ d2 w/ o# I8 iSpread, 展布' m2 S7 O8 |( u) ~8 `! J
SPSS(Statistical package for the social science), SPSS统计软件包 y* D8 Y/ v; [# k& d* g1 f2 B% R
Spurious correlation, 假性相关
. P5 L3 s4 {- }1 oSquare root transformation, 平方根变换
6 \9 `( Y! }: u! l! ~' f, X) K6 [& cStabilizing variance, 稳定方差
9 _ S5 C8 t D: ]Standard deviation, 标准差
; E- M: z% N* tStandard error, 标准误% v5 C5 o, h4 E4 u
Standard error of difference, 差别的标准误4 z. L+ ?0 @# \& e( h+ j5 C7 Y9 u
Standard error of estimate, 标准估计误差 ]; O3 n* ~( w' y
Standard error of rate, 率的标准误+ r* E. z+ t: c0 g: i1 a5 D
Standard normal distribution, 标准正态分布3 B8 q; `. e3 ]/ G7 M _) e
Standardization, 标准化4 G1 t0 k/ K; m- ]* Y( g! H, {' u
Starting value, 起始值! f; Q* Y- p. ^& S
Statistic, 统计量* E0 ]9 p1 f7 u* i
Statistical control, 统计控制
6 \! K$ M% _. EStatistical graph, 统计图3 P8 a& z* N3 q
Statistical inference, 统计推断
0 Z! W! Z$ w8 m- GStatistical table, 统计表3 n, A. S' J/ o- @3 g4 |1 A9 }
Steepest descent, 最速下降法0 O7 t0 A7 ]' ?& n9 ?
Stem and leaf display, 茎叶图6 [, M \9 _1 |$ z" ~
Step factor, 步长因子
1 `' _7 L# T, K& VStepwise regression, 逐步回归: h, {0 a/ n- w; O! O6 C. {8 h
Storage, 存
1 [9 X3 x/ z% \+ e, f: g( VStrata, 层（复数）8 ^+ o% d |) D% n
Stratified sampling, 分层抽样
$ \; _+ P, d. Y2 `0 X5 H4 m& HStratified sampling, 分层抽样1 y. T: ?( b; S S: d5 j0 I
Strength, 强度8 P) W; l6 H$ U4 `: l5 l- i% G
Stringency, 严密性
' \3 ]2 Y$ B$ ?3 a7 e# N6 z1 iStructural relationship, 结构关系
0 A6 G5 c- m! }8 Z( T3 ]1 s9 I% uStudentized residual, 学生化残差/t化残差
( F9 p3 _" g1 C; hSub-class numbers, 次级组含量) L( c. Q0 O( q3 Z+ @! K
Subdividing, 分割: R: S0 V+ L" f* G7 T
Sufficient statistic, 充分统计量7 Z0 y1 l, w6 Q% z. G
Sum of products, 积和
( w+ ?" ]% {. j/ ~. m. ?Sum of squares, 离差平方和
# m6 o- O! j6 [* |8 \7 ?3 {Sum of squares about regression, 回归平方和
) g$ W3 f$ ]2 \* \( X6 o) @Sum of squares between groups, 组间平方和! `9 E0 S& U F4 Y% ~. ]. d1 j% H
Sum of squares of partial regression, 偏回归平方和9 f- `3 A% x' T H' s
Sure event, 必然事件
B3 O; S2 f$ _4 F8 H2 W( oSurvey, 调查8 S7 N3 _% @1 }
Survival, 生存分析
+ @6 s. r y4 ISurvival rate, 生存率
9 g# d) }. V3 W" X: F) }Suspended root gram, 悬吊根图 Y; q9 m7 E3 ~0 a& S* r6 ^
Symmetry, 对称% R W3 v8 H# ~
Systematic error, 系统误差
' g2 W* E9 y5 E' nSystematic sampling, 系统抽样
) T- u3 F# L/ aTags, 标签
( @% W+ p6 D! I/ X. c. Y& z! CTail area, 尾部面积
2 U) \& L, L1 n2 r' C% QTail length, 尾长
, h q8 Y4 l4 W0 r9 a; BTail weight, 尾重
/ D* O, ]7 p3 F+ MTangent line, 切线3 ?8 q/ |7 K& F( |& ]! d( N
Target distribution, 目标分布
7 c2 Q7 O4 R' D+ J- N- HTaylor series, 泰勒级数
4 v7 _: E% z6 gTendency of dispersion, 离散趋势. F5 |% `" W( J7 f; ~
Testing of hypotheses, 假设检验0 A+ @' b: t3 F4 I, V& j
Theoretical frequency, 理论频数
( I+ a% A3 ~* _, s# h9 V$ eTime series, 时间序列
; O% o+ S; W% {Tolerance interval, 容忍区间. _; [+ c6 F! ^3 T0 @* ~, `3 D
Tolerance lower limit, 容忍下限! i/ `( o$ u7 X C
Tolerance upper limit, 容忍上限
, Z& R% y" W/ b4 e6 h( ]Torsion, 扰率
" l/ B- V+ `0 e: F& n8 f, jTotal sum of square, 总平方和
) ^4 }, k: ]) P8 ?Total variation, 总变异1 C; [6 y$ T! {1 j5 E0 \6 E& s
Transformation, 转换; n/ e9 Z- p$ L$ A9 l
Treatment, 处理* O+ X6 [, X1 s3 s; x( P( F( u
Trend, 趋势
- B& y/ G9 K) P) yTrend of percentage, 百分比趋势
0 A* Y; f5 j$ K5 v, N3 `/ n- LTrial, 试验9 o; M; B, C$ A
Trial and error method, 试错法1 _5 h' j. B3 S5 g2 S: e+ `
Tuning constant, 细调常数0 X5 \% v4 o+ z, S
Two sided test, 双向检验
0 @% o3 ?5 P- A7 r9 ?5 gTwo-stage least squares, 二阶最小平方7 k" [8 S5 O( N8 j
Two-stage sampling, 二阶段抽样
* Q2 @( x6 p9 q. I. u/ zTwo-tailed test, 双侧检验 w- K. c- t' }- l3 S$ G
Two-way analysis of variance, 双因素方差分析
0 E8 R0 e& S( H8 nTwo-way table, 双向表- N4 j5 d, P/ C
Type I error, 一类错误/α错误. A S3 G, b# f
Type II error, 二类错误/β错误
9 t( N% ]) C: {3 I. O- s2 w8 `3 IUMVU, 方差一致最小无偏估计简称
% }: r+ V. n0 R- j& ?1 P8 Y9 I& Y+ ]Unbiased estimate, 无偏估计
" f) o4 t2 K0 o* i7 O gUnconstrained nonlinear regression , 无约束非线性回归8 g, I& ^" M! l, f/ b: c4 |
Unequal subclass number, 不等次级组含量. D( ?6 u; D9 c9 ^. u, X
Ungrouped data, 不分组资料
W6 f2 P$ k# {. r) [2 g* f7 \Uniform coordinate, 均匀坐标
) W' p+ w8 _) qUniform distribution, 均匀分布6 D# N! ^9 j" a4 y% ~- U
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计, \+ m; \2 Z) E9 U; U
Unit, 单元
, b# T; T! `& i+ KUnordered categories, 无序分类/ B; |" `, i) f: o" e, Y9 c" N, _; v; h
Upper limit, 上限8 x0 f2 c% v; L" T, ?0 W) U6 {
Upward rank, 升秩
7 m2 v* ^8 ~" C' N" f4 gVague concept, 模糊概念. @, J; @* a! s' ]6 ]
Validity, 有效性
8 |2 ?7 i& R( L" g; Q) A4 ~# yVARCOMP (Variance component estimation), 方差元素估计( |. a6 U6 e, [: Y; \
Variability, 变异性9 ^3 C' ^+ Q9 O7 Y( e
Variable, 变量! X4 [4 @; [2 R) f0 c: ]
Variance, 方差
, s/ d0 n9 L- m1 S* W5 YVariation, 变异
4 g; C3 b; C& E* U9 K1 T9 l# r0 \Varimax orthogonal rotation, 方差最大正交旋转/ H3 B: L% L' t* D1 d* \
Volume of distribution, 容积
8 X/ d+ d* a+ a$ }% N3 z P aW test, W检验) H' q! V/ Z6 ?( }8 L
Weibull distribution, 威布尔分布, q0 F6 B: R' U, V% {7 r
Weight, 权数7 \- w6 W3 S5 Q' T. F1 n% z
Weighted Chi-square test, 加权卡方检验/Cochran检验
- J! I9 h& Z9 d! X- s4 O( VWeighted linear regression method, 加权直线回归
0 @( V0 V1 W) F% IWeighted mean, 加权平均数
% m% e: A2 f0 c! ]; P- IWeighted mean square, 加权平均方差
7 r. _6 Q5 U4 a4 e, }Weighted sum of square, 加权平方和9 d+ f. O) |) ~3 O$ g
Weighting coefficient, 权重系数& N. ~ P" M3 k
Weighting method, 加权法 0 [4 X7 {4 j% L# L* U3 ]. a- M
W-estimation, W估计量
2 n8 q; t8 N! v1 `5 IW-estimation of location, 位置W估计量7 E& a7 G5 V/ p
Width, 宽度
; G, r9 A& w1 Q1 x* g0 WWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
8 J' Y+ o! a8 k: K& D. KWild point, 野点/狂点
# ]* V$ h8 S3 J# c$ q aWild value, 野值/狂值
! T9 e$ l+ ` Y6 {( l, LWinsorized mean, 缩尾均值' ~ L$ A% C' c; q; X* i3 b
Withdraw, 失访 4 H( Q) j$ n! |2 x: O. i4 O9 n- ?
Youden's index, 尤登指数
; ^" v, d6 P9 q3 C9 }, B; ]Z test, Z检验: e& ?- z- Q- j5 v: j
Zero correlation, 零相关2 F& v/ L% K9 ^( J$ _
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
